The Commodification of Behavior in the Age of AI
Exploring one of the most ethically complex and socially impactful issues of our time, beyond surface-level data ownership and privacy critiques
The commodification of human behavior is a defining feature of the digital age, driven by the rise of artificial intelligence (AI) and the insatiable demand for behavioral data. Every action we take online—whether it's a search, a click, a purchase, or even a momentary pause on a video—is transformed into a monetizable data point. Tech corporations collect, analyze, and sell these behaviors, using increasingly sophisticated AI algorithms designed to predict, influence, and monetize our every move.
While the idea of compensating individuals for their data has gained traction, I believe such a solution fails to confront the far more pervasive and ethically troubling issue: the very transformation of human behavior into an economic asset.
As I continue to explore the ethical dimensions of AI, it becomes increasingly clear that while a growing body of research has explored AI ethics, surveillance capitalism, and data privacy, the commodification of behavior itself remains under-theorized and largely unchallenged in academic discourse.
The core issue goes beyond questions of ownership or privacy; it strikes at the heart of how AI systems manipulate and exploit human behavior for profit, often without individuals' full awareness or consent.
The complexities of these systems—and their impact on personal autonomy, societal power dynamics, and marginalized communities—demand a far more rigorous and multidisciplinary investigation than what current scholarship currently offers.
The Limits of Current Research
Overemphasis on Privacy and Data Ownership: Much of the discourse around AI ethics, particularly in the wake of works like Shoshana Zuboff's The Age of Surveillance Capitalism, has centered on data privacy and ownership. Zuboff’s work has been instrumental in illuminating the vast power asymmetries between corporations and individuals, particularly in terms of data exploitation. However, this focus on data ownership and privacy, while crucial, often neglects the more subtle and insidious ways in which AI commodifies behavior itself. The transformation of behavior into data not only invades privacy but also erodes autonomy, as our actions are increasingly shaped by systems designed to keep us engaging, consuming, and producing more profitable data points.
Failure to Critically Engage with Behavioral Manipulation: A significant gap exists in research that critically examines how AI-driven systems manipulate behavior in ways that transcend traditional concerns of privacy and fairness. Scholars like Kate Crawford and Meredith Whittaker have made strides in highlighting the social and environmental harms of AI, along with advocating for greater transparency and regulation. Yet, the conversation often stops short of interrogating the deeper implications of behavioral commodification: how AI shapes human actions not merely for optimization but for alignment with corporate interests, often at the expense of individual autonomy and well-being. Current research frequently lacks a robust critique of how AI systems distort behavior for financial gain under the guise of "better user experiences."
Limited Interdisciplinary Engagement: While fields such as behavioral economics, psychology, and sociology have each contributed to understanding how digital platforms influence behavior, much of the existing work remains confined within disciplinary silos. Economists may explore the incentives behind data collection, psychologists might study the cognitive effects of digital environments, and ethicists could focus on issues of consent and autonomy. Rarely, however, do these fields intersect to provide a comprehensive analysis of how behavior is commodified and monetized by AI systems. This fragmented approach limits our ability to develop effective countermeasures or alternative frameworks to mitigate these issues.
Inadequate Attention to Power and Exploitation: One of the most profound concerns about the commodification of behavior by AI systems is how it reinforces structural inequalities and extends capitalist exploitation into new digital realms. Yet, existing research often lacks a critical examination of these dynamics. Marginalized communities, already vulnerable to predatory data practices, are disproportionately affected by these systems. Scholars like Ruha Benjamin and Safiya Umoja Noble have exposed the racialized and gendered dimensions of algorithmic bias, but the commodification of behavior itself—particularly among marginalized populations—remains underexplored. This gap leaves blind spots in our understanding of how AI systems perpetuate exploitation, often under the guise of efficiency and personalization.
Engaged Principal Investigators and Current Efforts
Despite the need for more rigorous inquiry into behavior commodification, there are some engaged principal investigators (PIs) and research efforts beginning to tackle these issues:
Shoshana Zuboff (Harvard Business School) has provided foundational insights into how surveillance capitalism operates. Her work primarily deals with data exploitation from a macroeconomic perspective, with less focus on the nuanced ways in which AI systems directly influence and commodify individual behaviors.
Kate Crawford (AI Now Institute) has contributed significantly to the critical discourse on AI’s environmental and social impacts, advocating for deeper accountability and transparency. However, her work does not fully unpack the intricacies of behavior commodification at the micro-level, particularly how AI systems manipulate user actions for profit.
MacArthur grantee Ruha Benjamin (Princeton University) and Safiya Umoja Noble (UCLA) have engaged critically with the racialized and gendered dynamics of algorithmic bias, offering crucial insights into how AI systems exacerbate social inequalities. Their work opens up new avenues for understanding how marginalized communities are disproportionately targeted by AI-driven commodification practices, but further research is needed to explore how behavior itself becomes a tool for exploitation in these contexts.
The Need for a New Research Direction
In my view, addressing the commodification of behavior in AI systems requires moving beyond existing frameworks and engaging with the deeper ethical, social, and political dimensions of this phenomenon. This involves several critical steps:
Interdisciplinary Integration: A comprehensive understanding of behavior commodification requires collaboration across fields such as behavioral economics, AI ethics, psychology, sociology, and political economy. By bringing these disciplines into dialogue, researchers can develop a more nuanced picture of how AI systems manipulate behavior and commodify human actions, as well as the broader consequences of these practices for society.
Behavioral Manipulation and Autonomy: Focused research is needed to critically examine how AI-driven platforms influence and shape human behavior in ways that are often invisible to users. This requires an exploration of how recommendation engines, predictive algorithms, and engagement-driven systems subtly nudge users toward actions that align with corporate profit motives, undermining autonomy and potentially causing psychological harm.
Power and Exploitation: Future research must critically engage with how AI commodifies behavior to reinforce existing power structures and deepen social inequalities. It is crucial to explore how these systems disproportionately affect marginalized communities, commodifying their behaviors for profit while offering little in return. This requires a deep investigation into the exploitative dimensions of behavior commodification in the context of global capitalism.
Regulatory and Ethical Frameworks: Developing regulatory frameworks that not only protect data privacy but also address behavioral commodification is essential. These frameworks must focus on transparency, algorithmic accountability, and safeguarding individual autonomy from the exploitative tendencies of AI systems. There should also be a push towards exploring alternative models for AI development—ones that prioritize human dignity and ethical design over short-term profit.
The commodification of behavior by AI systems is one of the most ethically complex and socially impactful issues of our time. While current research has made strides in addressing data privacy and algorithmic bias, it has yet to fully engage with the deeper implications of behavior commodification.
The time is ripe for a critical exploration of how AI systems shape and monetize human actions, and what this means for autonomy, power, and equality in a rapidly digitizing world.
In advocating for a multidisciplinary approach, I hope to contribute to a shift in the way we understand and address these issues, challenging the power dynamics inherent in AI-driven commodification practices.
By expanding the scope of research beyond surface-level discussions of privacy and data ownership, we can begin to develop frameworks that protect individual autonomy, resist exploitation, and promote more ethical uses of AI.